Wild Watch

• 

• 

• 

• 

  Added Maps Functionality

Inspiration

Recent surge in wildfires pushed us to build an AI-driven early warning system to protect communities before disasters strike.

What it does

WildWatch predicts fire risks and manages firefighting resources through a real-time dashboard showing fire incidents, risk levels, and resource status.

How we built it

React frontend with Tailwind CSS, Flask backend, and Random Forest ML model for risk prediction, all integrated into one smooth system.

Challenges we ran into

Wrestling with CORS issues, fine-tuning ML models, and crafting a resource allocation system that actually works when seconds count.

Accomplishments that we're proud of

Built a working fire prediction system that first responders can actually use, wrapped in a clean interface that makes sense at a glance.

What we learned

Merging AI with real-world emergency response is tricky but game-changing. Learned tons about ML deployment and making complex systems user-friendly.

What's next for Wild Watch

Mobile app, real-time weather data, interactive maps, and a local alert system to notify both emergency teams and nearby residents when risks spike.

Built With

• flask
• framer-motion
• pandas
• react
• scikit-learn
• tailwindcss
• typescript
• vite